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The flexibly thin film grid pressure sensor is mainly used to detect the interface pressure distribution between touching objects. Aim at larger measurement error, the strip double sensing layer pressure sensor are designed and fabricated and tested.

Defects and characteristic of the flexibly thin film grid pressure sensor based on piezoresistive effect are analyzed and pointed out in this paper. After comparison of four sensors, the strip double sensing layer pressure sensor was thought to be best.

Experiment shows that the strip double sensing layer pressure sensor could eliminate the measurement error basically and illustrates the validity of measuring the interface pressure distribution between area touching objects.

In this paper, only the strip double sensing layer pressure sensor was used to verify the validity of measuring the static interface pressure distribution between peach and platform. But there also exists some problems such as the adhering reliability of electrode and the unevenness of sensing layer. These problems could be overcome in the future research if the fabricating procedure and ingredient of material could be adjusted correctly.

The strip double sensing layer pressure sensor could be applied to detect the static interface pressure distribution such as peach pressure distribution. For dynamic measurement, this research needs to be done further.

Strip double sensing layer pressure sensor with simple “interlayer” structure and with low manufacture cost is presented to basically eliminate the measurement error of interface pressure distribution of original sensor.

There are many cases where top management either missed or almost missed detecting or interpreting a major change in the environment that might have led them to a major setback. We propose a model of sensing in hierarchical organizations that describes a sequence of sensing and detecting changes in the environment, followed by successive stages of perception, interpretation, and finally action. We model an organization as a complex signal detection system, where the flow of information among members of the organization is constrained by two elements: the structure of the organization, which is defined by who reports to whom, and the attentional and cognitive limitations of the individuals. We infer the probability of sensing over time for different levels of environmental shocks and different organizational structures. By focusing on the (un)reliability of sensing and the information flow in different organizational structures, we are able to provide preliminary analysis of the trade-offs among cognitive limitations, speed of detection, modes of information flow, and the resulting performance measure of delay, false-alarms, and true detections.

Tactile sensing is the process of determining physical properties and events through contact with objects in the world. The purpose of this paper is to establish a novel design of an adaptive neuro-fuzzy inference system (ANFIS) for estimation of contact position of a new tactile sensing structure.

The major task is to investigate implementations of carbon-black-filled silicone rubber for tactile sensation; the silicone rubber is electrically conductive and its resistance changes by loading or unloading strains.

The sensor-elements for the tactile sensing structure were made by press-curing from carbon-black-filled silicone rubber. The experimental results can be used as training and checking data for the ANFIS network.

This system is capable to find any change of contact positions and thus indicates state of the current contact location of the tactile sensing structure. The behavior of the use silicone rubber shows strong non-linearity, therefore, the sensor cannot be used for high accurate measurements. The greatest advantage of this sensing material lies in its high elasticity.

With the increasing development of the surgical robots, the opto-mechatronic technologies are more potential in the robotics system optimization. The optic signal plays an important role in opto-mechatronic systems. This paper aims to present a review of the research status on fiber-optic-based force and shape sensors in surgical robots.

Advances of fiber-optic-based force and shape sensing techniques in the past 20 years are investigated and summarized according to different surgical requirement and technical characteristics. The research status analysis and development prospects are discussed.

Compared with traditional electrical signal conduction, the phototransduction provides higher speed transmission, lower signal loss and the immunity to electromagnetic interference in robot perception. Most importantly, more and more advanced optic-based sensing technologies are applied to medical robots in the past two decades because the prominence is magnetic resonance imaging compatibility. For medical robots especially, fiber-optic sensing technologies can improve working security, manipulating accuracy and provide force and shape feedback to surgeon.

This is a new perspective. This paper mainly researches the application of optical fiber sensor according to different surgeries which is beneficial to learn the great potential of optical fiber sensor in surgical robots. By enumerating the research progress of medical robots in optimization design, multimode sensing and advanced materials, the development tendency of fiber-optic-based force and shape sensing technologies in surgical robots is prospected.

The purpose of this paper is to provide a thin tactile force sensor array based on conductive rubber and to offer descriptions of the sensor design, fabrication and test.

The sensor array consists of a sandwich structure. Sensing elements are distributed discretely in the sensor. Each sensing element has two electrodes and a piece of conductive rubber with piezoresistive property. The electrodes, as well as the conductive trace for signal transmission, are printed on the substrate layer by the screen printing technique. A scanning circuit based on zero potential method and an experimental set‐up based on balance to characterize the sensor array are designed and implemented in the test of the sensor array.

Experimental results verify the validity of the sensor array in measuring the vertical tactile force between the sensing elements and the object.

In this paper, all the sensors are tested without calibration procedures and the procedure of the dynamic test is implemented by manual operation.

The sensor array could be applied to measure the plantar force for gait detection in clinical applications.

The paper presents a tactile force sensor array with discrete sensing elements to essentially restrict the cross‐talk among sensing elements. This paper will provide many practical details that can help others in the field.

The aim of this paper is to investigate implementations of carbon‐black filled silicone rubber for tactile sensation.

The sensor‐elements for this tactile sensing structure were made by press‐curing from carbon‐black filled silicone rubber.

The behaviour of the silicone rubber shows strong non‐linearity, therefore, the sensor cannot be used for accurate measurements. The greatest advantage of this material lies in its high elasticity.

A new method for artificial tactile sensing skin for robotic applications.

Gesture recognition plays an important role in many fields such as human–computer interaction, medical rehabilitation, virtual and augmented reality. Gesture recognition using wearable devices is a common and effective recognition method. This study aims to combine the inverse magnetostrictive effect and tunneling magnetoresistance effect and proposes a novel wearable sensing glove applied in the field of gesture recognition.

A magnetostrictive sensing glove with function of gesture recognition is proposed based on Fe-Ni alloy, tunneling magnetoresistive elements, Agilus30 base and square permanent magnets. The sensing glove consists of five sensing units to measure the bending angle of each finger joint. The optimal structure of the sensing units is determined through experimentation and simulation. The output voltage model of the sensing units is established, and the output characteristics of the sensing units are tested by the experimental platform. Fifteen gestures are selected for recognition, and the corresponding output voltages are collected to construct the data set and the data is processed using Back Propagation Neural Network.

The sensing units can detect the change in the bending angle of finger joints from 0 to 105 degrees and a maximum error of 4.69% between the experimental and theoretical values. The average recognition accuracy of Back Propagation Neural Network is 97.53% for 15 gestures.

The sensing glove can only recognize static gestures at present, and further research is still needed to recognize dynamic gestures.

A new approach to gesture recognition using wearable devices.

This study has a broad application prospect in the field of human–computer interaction.

The sensing glove can collect voltage signals under different gestures to realize the recognition of different gestures with good repeatability, which has a broad application prospect in the field of human–computer interaction.

This paper aims to clarify the relationship between the performance of the metal nanoparticles and the sensitivity of the fiber surface plasma resonance (SPR) sensor. It proposes modeling the sensing effects of a single-mode fiber SPR sensor with a cone angle structure decorated with metal nanoparticles. This study uses the metal nanoparticles to the realize enhanced sensitivity of refractive index sensing.

This paper opted for an exploratory study using a simulation approach of finite-difference time-domain (FDTD). Specifically, the effect of size, the material and the shape of the metal nanoparticle on sensing performance are investigated theoretically.

In conclusion, it is evident that the localized SPR (LSPR) effect weakens as the diameter of the gold nanosphere increases, the SPR effect enhances and the SPR sensitivity increases first and then decreases. The metal nanoparticle with the different materials and different shapes also have different LSPR and SPR sensitivity and wavelength length dynamic range. The investigation shows that, by changing parameters, the reflection spectra of the fiber SPR sensor exhibit an obvious transition from LSPR to SPR characteristics, and enhanced sensitivity of the refractive index is realized.

This paper fulfills an identified need to study how the sensitivity of the fiber SPR sensor can be enhanced by the metal nanoparticle. After the optimization of parameters, the sensitivity of 5,140 nm/RIU is achieved, which provides a new research direction for sensitivity enhancement of fiber SPR sensor.

The purpose of this study is to evaluate different 3D structures for humidity sensing that will enable the fabrication of complex geometries with high moisture sensitivity.

Humidity sensors based on alumina ceramics were fabricated using direct ink write (DIW) technique. Different engineered surface area, polymer binder ratio and post-processing treatment were considered to increase moisture sensitivity.

It was found that the binder ratio plays an important role in controlling the rheology of the paste during printing and determining the pore size after post-processing treatment. The sensibility of the fabricated humidity sensor was investigated by measuring its capacitance response toward relative humidity (RH) varying from 40% to 90% RH at 25°C. It is shown that using 3D lattice design, printed alumina humidity sensor could improve sensitivity up to 31.6 pF/RH%, over an order of magnitude higher than solid alumina.

Most of the alumina humidity sensors available are films in nature because of manufacturing difficulties, which limited its potential of higher sensitivity, and thus broader applications. In this paper, a novel 3D alumina humidity sensor was fabricated using DIW 3D printing technology.

The purpose of this paper is to provide a contemporary look at the current state‐of‐the‐art in wireless sensor networks (WSNs) for structure health monitoring (SHM) applications and discuss the still‐open research issues in this field and, hence, to make the decision‐making process more effective and direct.

This paper presents a comprehensive review of WSNs for SHM. It also introduces research challenges, opportunities, existing and potential applications. Network architecture and the state‐of‐the‐art wireless sensor communication technologies and standards are explained. Hardware and software of the existing systems are also clarified.

Existing applications and systems are presented along with their advantages and disadvantages. A comparison landscape and open research issues are also presented.

The paper presents a comprehensive and recent review of WSN systems for SHM applications along with open research issues.